DBMS > Apache IoTDB vs. FileMaker vs. NSDb vs. OrigoDB vs. PostGIS

System Properties Comparison Apache IoTDB vs. FileMaker vs. NSDb vs. OrigoDB vs. PostGIS

Editorial information provided by DB-Engines

Name

Description

An IoT native database with high performance for data management and analysis, deployable on the edge and the cloud and integrated with Hadoop, Spark and Flink

FileMaker is a cross-platform RDBMS that includes a GUI frontend.

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

A fully ACID in-memory object graph database

Spatial extension of PostgreSQL

Primary database model

Time Series DBMS

Relational DBMS

Time Series DBMS

Document store
Object oriented DBMS

Spatial DBMS

Secondary database models

Relational DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	1.31
Rank	#164	Overall
	#14	Time Series DBMS

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	0.08
Rank	#369	Overall
	#40	Time Series DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#19	Object oriented DBMS

Score	21.72
Rank	#29	Overall
	#1	Spatial DBMS

Website

iotdb.apache.org

www.claris.com/filemaker

nsdb.io

origodb.com

postgis.net

Technical documentation

iotdb.apache.org/UserGuide/Master/QuickStart/QuickStart.html

www.claris.com/resources/documentation

nsdb.io/Architecture

origodb.com/docs

postgis.net/documentation

Developer

Apache Software Foundation

Claris

a subsidiary of Apple

Robert Friberg et al

Initial release

2018

1983

2017

2009

under the name LiveDB

2005

Current release

1.1.0, April 2023

19.4.1, November 2021

3.4.2, February 2024

License

Commercial or Open Source

Open Source

Apache Version 2.0

commercial

Open Source

Apache Version 2.0

Open Source

GPL v2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Java, Scala

Server operating systems

All OS with a Java VM (>= 1.8)

iOS

client part only
Linux
OS X
Windows

Linux
macOS

Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

User defined using .NET types and collections

yes

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

A http query request can return the data in XML format

can be achieved using .NET

yes

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL-like query language

yes

via plugins

SQL-like query language

yes

APIs and other access methods

JDBC
Native API

Filemaker WebDirect
JDBC
ODBC

gRPC
HTTP REST
WebSocket

.NET Client API
HTTP API
LINQ

Supported programming languages

C
C#
C++
Go
Java
Python
Scala

PHP

Java
Scala

.Net

Server-side scripts

Stored procedures

yes

user defined functions

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning (by time range) + vertical partitioning (by deviceId)

none

Sharding

horizontal partitioning

client side managed; servers are not synchronized

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication methods; using Raft/IoTConsensus algorithm to ensure strong/eventual data consistency among multiple replicas

Source-replica replication, warm standby

since Version 14

Source-replica replication

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

Integration with Hadoop and Spark

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Strong Consistency with Raft

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

depending on model

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

yes

Write ahead log

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

yes

simple rights management via user accounts and connection to external directory services

Role based authorization

yes

based on PostgreSQL

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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